By chromatin state
TssA (1)
chromhmm.state <- "TssA"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`1_TssA`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

TssAFlnk (2)
chromhmm.state <- "TssAFlnk"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`2_TssAFlnk`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
ggvenn.lst[[1]]

TxWk (5)
chromhmm.state <- "TxWk"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`5_TxWk`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[3]], ggvenn.lst[[4]], ncol = 2))

EnhG (6)
chromhmm.state <- "EnhG"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`6_EnhG`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[3]], ggvenn.lst[[4]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[5]], ncol = 1))

Enh (7)
chromhmm.state <- "Enhancer"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`7_Enh`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[3]], ggvenn.lst[[4]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[5]], ncol = 1))

BivFlnk (11)
chromhmm.state <- "BivFlnk"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`11_BivFlnk`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
ggvenn.lst[[1]]

EnhBiv (12)
chromhmm.state <- "EnhBiv"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`12_EnhBiv`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

ReprPC (13)
chromhmm.state <- "ReprPC"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`13_ReprPC`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[3]], ggvenn.lst[[4]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[5]], ncol = 1))

ReprPCWk (14)
chromhmm.state <- "ReprPCWk"
chromhmm.snps.df <- chromhmm.cpg.state.lst.df$`14_ReprPCWk`
chromhmm.snps.df <- left_join(chromhmm.snps.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- chromhmm.snps.df$Salas %>%
unique()
blood.cell.types.of.interest <- blood.cell.types.of.interest[blood.cell.types.of.interest %in% cell.types.of.interest]
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.snps.df,
dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[3]], ggvenn.lst[[4]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[5]], ncol = 1))

All states
###### Overlap between two cell type-specific analysis
chromhmm.state <- "all significant states"
chromhmm.cpgs.df <- chromhmm.cpg.state.lst.df %>%
bind_rows()
chromhmm.cpgs.df <- left_join(chromhmm.cpgs.df, epigenome.blood.map.df[, .(EID, Salas)], by = c(eid = "EID"))
blood.cell.types.of.interest <- c("Bmem+Bnv", "CD4mem", "CD4nv", "CD8mem", "Neu")
chromhmm.state.of.interest <- c("1_TssA", "2_TssAFlnk", "5_TxWk", "6_EnhG", "7_Enh", "11_BivFlnk", "12_EnhBiv",
"14_ReprPC", "14_ReprPCWk")
ggvenn.lst <- lapply(blood.cell.types.of.interest, GetVennDiagram, chromhmm.snps.df = chromhmm.cpgs.df[state %in%
chromhmm.state.of.interest, ], dex.blood.types.snps.df = dex.blood.types.cpgs.df, veh.blood.types.snps.df = veh.blood.types.cpgs.df,
chromhmm.state = chromhmm.state)
grid.arrange(arrangeGrob(ggvenn.lst[[1]], ggvenn.lst[[2]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[3]], ggvenn.lst[[4]], ncol = 2))

grid.arrange(arrangeGrob(ggvenn.lst[[5]], ncol = 1))
